The pressure layer represents biological pressure caused by introduction of non-indigenous species. The data is obtained from core indicator Trend in the arrival of new non-indigenous species (BSEP 129b: http://www.helcom.fi/Lists/Publications/BSEP129B.pdf). For the Baltic Sea Impact Index, the layer was normalized.

This dataset represents the underlying data on core indicator Abundance of waterbirds in the breeding season 2018. The data is resulting from a data call carried out by HELCOM for State of the Baltic Sea report. Attribute information: "YEAR" = Year of the observation "SPECIES" = Species accepted scientific name "ABUNDANCE" = Abundance count "Country" = Country of observation "SITECODE" = Unique site code

Broad-scale habitat maps for the Baltic Sea have been produced in the EUSeaMap project in 2016. For German and Estonian marine areas, national (more accurate) datasets were used. German data included both substrate and light information (division into infralittoral/circalittoral). Estonian data included only substrate and the division into light regimes was obtained from the EuSeaMap data. Here, the habitat class “infralittoral mud” includes classes “Fine mud”, “Mud to sandy mud” and “Sandy mud” of the original data, in the infralittoral zone. The original polygon maps have been converted to 1 km x 1km grid. The scale of the substrate data used in broad-scale habitat maps varies from 1:250 000 to 1:1M (data from EMODnet Geology). Coarser resolution data has been used in areas, where 1: 250 000 substrate data has not been available. Due to different scales used, the habitat classes may show different sized patterns in different areas.

The map of sprat relative abundance is mainly based on Baltic International acoustic surveys (BIAS), years 2011-2016, (ICES WGBIFS reports), reported as millions of sprat per ICES rectangle. The BIAS surveys cover almost the whole area where sprat is commonly encountered. Outside BIAS area, sprat landings data was used to complement the data. For ICES rectangles surveyed by BIAS, values shown are the mean values per ICES rectangle based on BIAS data, average for 2011-2016. For ICES rectangles not surveyed by BIAS, values are calculated as: MAX-value x Weighting factor. The weighting factor is specific to each ICES rectangle, calculated as the ratio between the commercial landings in that rectangle and the commercial landings in the ICES rectangle with highest landings (based on averages for 2011-2015). MAX-value = millions of sprat according to BIAS in the ICES rectangle with highest landings. ICES rectangles outside the BIAS survey area with no reported sprat landings were given the value 0. The abundance values / ICES rectangle were divided by the area of the rectangle to obtain values per 1km2, and then converted to 1 km x 1km grid cells. Values were first log transformed and then normalised.

This dataset was collected by HELCOM Secretariat during the HELCOM MORE project and represents monitoring stations in the Baltic Sea. This dataset contains all nutrient stations in the Baltic Sea as reported to the HELCOM MORE project.

The data set is showing areas where fish farming takes place in the Baltic Sea area as points. The data set used for the BRISK project (Sub-regional risk of spill of oil and hazardous substances in the Baltic Sea, http://www.brisk.helcom.fi/). The dataset has been produced by COWI (http://www.cowi.dk) based on data collected by HELCOM from Baltic countries (Finland: Copyright SYKE) and by Germany. The dataset includes data provided by the BRISK Project Partner organisations from various Baltic Sea countries. The detailed documentation of what partner provided what data is given in the Annex of the document: 70618-3.1.2.2 Data Collection Report. Fish farms are stationary and therefore the floating oil or chemicals may cause great damage to the reared fish.

Summary This dataset was collected by HELCOM Secretariat during the HELCOM MORE project and represents monitoring stations in the Baltic Sea Description This dataset contains all shared nutrient stations in the Baltic Sea as reported to the HELCOM MORE project. It was collected and published at the beginning of 2013.The data came originally from the CORESET project. Contracting Parties were then asked to complete and check the info.

This dataset describes fishing effort (hours/c-square) for longlines in 2011 based on VMS/Log book data processed by ICES Working Group on Spatial Fisheries Data (WGSFD). HELCOM requires spatially explicit information on fishing activity affecting the Baltic Sea marine ecosystem for policy purposes. In order to obtain this information a joint ICES/HELCOM/OSPAR data call was issued to relevant authorities of contracting parties to deliver information on fishing activity based on VMS/Log book data. The raw data was submitted to ICES and processed to advice data products by ICES Working Group for Spatial Fisheries (WGSFD) as requested by HELCOM. Processing of the raw data requires specific resources, knowledge and guarantee of anonymity for specific vessels, thus the process was done by ICES WGSFD following Conditions for VMS data use. In 2015 ICES collated Vessel Monitoring System (VMS) and logbook data received; data from Russia were not received. ICES provided to HELCOM advice as fishing abrasion pressure maps as well as fishing effort maps. HELCOM secretariat did the following processing to the data: - Conversion to ETRS89LAEA coordinate system - Added feature and attribute "Reported" to display unreported areas. Dataset attribute information: c-square: Unique reference of the c-square polygon mid_lat: latitude coordinate of the centroid of c-square inWGS84 decimal degrees mid_lon: longitude coordinate of the centroid of c-square inWGS84 decimal degrees Year: Year of fishing activity quarter: Quarter of the year, if applicable geargroup: Fishing gear group (Effort maps) SubsurfSAR: Subsurface swept area ratio (Intensity maps) SurfSAR: Surface swept area ratio (Intensity maps) Fishing_ho: Total fishing effort in hours within c-square (Effort maps) Reported: Yes=Reported data. No= No reported data (area that does not contain effort/intensity value due to lack of reported data.

Introduction of radionuclides is based on HELCOM MORS discharge data (2016-2020) . Annual averages of CO60, CS137 and SR90 from the period 2016-2020 per nuclear power plant. Gradual buffer around outlet to 10km distance (Type B decline). 10 km buffer with linear decline composed of 5 rings from discharges of radioactive substances (Type B decline)12.

Pressure layer combines all human activities that cause changes to hydrological conditions. The human activities were presented as point data which were given spatial extents (given below). The pressure value was given as the proportion of the grid cell under the pressure. Water course modification: 1 km buffer[10]. Location of water course modifications used for buffer. Overlaps removed and areas of buffer calculated per each grid cell. The final value was the area of the buffer in each individual cell. Wind farms: 300 m buffer around each turbine classified as operational, with linear decline (Type B decline), composed of 3 rings. Location of operational turbines as points were buffered and values given over linear decline. Oil platforms: 500 m buffer around each turbine with linear decline (Type B decline) composed of 5 rings. Location of oil platforms as points were buffered and values given over linear decline. Hydropower dams: A grid cell in the estuary. Locations of hydropower dams were crossed with rivers and the grid cell located in the end of the river was selected as presence (1) – those that are operational and produces energy. Other values in the grid were considered absence. [10] Extent based on wind farms and cables but expanded to 1 km because hydrological parameters are widely spreading. The human activity datasets were first processed separately covering the whole Baltic Sea and then summed together and overlapping areas were dissolved to remove double counting. Attenuation gradients are assigned to each layer as described above. Area effected decreases when distance from avtivity increases. Layer was normalized.